Show simple item record

dc.contributor.authorOttoboni, Kellie
dc.contributor.authorBernhard, Matthew
dc.contributor.authorHalderman, J. Alex
dc.contributor.authorRivest, Ronald L
dc.contributor.authorStark, Philip B.
dc.date.accessioned2021-02-23T16:08:09Z
dc.date.available2021-02-23T16:08:09Z
dc.date.issued2020-03
dc.identifier.isbn9783030437244
dc.identifier.isbn9783030437251
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttps://hdl.handle.net/1721.1/129973
dc.description.abstractWe present a method and software for ballot-polling risk-limiting audits (RLAs) based on Bernoulli sampling: ballots are included in the sample with probability p, independently. Bernoulli sampling has several advantages: (1) it does not require a ballot manifest; (2) it can be conducted independently at different locations, rather than requiring a central authority to select the sample from the whole population of cast ballots or requiring stratified sampling; (3) it can start in polling places on election night, before margins are known. If the reported margins for the 2016 U.S. Presidential election are correct, a Bernoulli ballot-polling audit with a risk limit of 5% and a sampling rate of p0=1% would have had at least a 99% probability of confirming the outcome in 42 states. (The other states were more likely to have needed to examine additional ballots). Logistical and security advantages that auditing in the polling place affords may outweigh the cost of examining more ballots than some other methods might require.en_US
dc.language.isoen
dc.publisherSpringer International Publishingen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/978-3-030-43725-1_16en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleBernoulli Ballot Polling: A Manifest Improvement for Risk-Limiting Auditsen_US
dc.typeBooken_US
dc.identifier.citationOttoboni, Kellie et al. "Bernoulli Ballot Polling: A Manifest Improvement for Risk-Limiting Audits." FC: International Conference on Financial Cryptography and Data Security, Lecture Notes in Computer Science, 11599, Springer International Publishing, 2020, 226-241. © 2020 International Financial Cryptography Association.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalLecture Notes in Computer Scienceen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-02-04T17:02:05Z
dspace.orderedauthorsOttoboni, K; Bernhard, M; Halderman, JA; Rivest, RL; Stark, PBen_US
dspace.date.submission2021-02-04T17:02:08Z
mit.journal.volume11599en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record